Explanation:
Correct Answer: C
Unsupervised learning involves training a model to discover data patterns without explicit guidance, while supervised learning involves training a model to make predictions or classify data using labeled examples.
A is incorrect: This reverses the definitions. Unsupervised learning actually involves training on unlabeled data, while supervised learning uses labeled data.
B is incorrect: Unsupervised learning recognizes data patterns without an explicit/predefined target, not necessarily to "classify" - that's typically a supervised task. Unsupervised learning may involve clustering or dimensionality reduction.
D is incorrect: This describes reinforcement learning (maximizing reward signal) versus supervised learning (minimizing loss function), not the distinction between unsupervised and supervised learning.
Ultimate access to all questions.
Which of the following best describes the main difference between unsupervised learning and supervised learning?
A
Unsupervised learning involves training a model on labeled data, while supervised learning involves training a model on unlabeled data.
B
Unsupervised learning involves training a model to make predictions, while supervised learning involves training a model to classify data.
C
Unsupervised learning involves training a model to learn from the data itself, while supervised learning involves training a model using explicit guidance from a human.
D
Unsupervised learning involves training a model to maximize a reward signal, while supervised learning involves training a model to minimize a loss function.
No comments yet.